MATLAB图像处理工具箱函数与应用详解

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"《Digital Image Processing Using MATLAB, 2nd Edition》附录A主要涵盖了Image Processing Toolbox中的所有函数以及书中自定义开发的新功能,这些新功能被称为DIPUM(Digital Image Processing Using MATLAB的首字母缩写)。附录分为两部分:A.1节列出了Toolbox中的所有函数和书中使用的自定义函数,而A.2节则列出了书中使用的所有MATLAB函数及其首次使用的页码,以便读者查找和理解。书中未使用的Toolbox函数用灰色破折号“—”表示,更多信息可在产品文档中找到。所有在A.2节列出的MATLAB函数都在书中有所应用,每个页码对应于该MATLAB函数的首次使用。函数按照与Image Processing Toolbox文档类似的类别进行大致分类,对于没有Toolbox类别的新功能(如小波)创建了新的类别。" 在《Digital Image Processing Using MATLAB, 2nd Edition》这本书中,作者Rafael C. Gonzalez、Richard E. Woods和Steven L. Eddins深入探讨了使用MATLAB进行数字图像处理的方法。书中提供的工具和函数涵盖了图像处理的多个核心领域,包括图像的获取、增强、分析、恢复、压缩和显示等。通过MATLAB这一强大的计算平台,读者能够实践各种图像处理技术。 附录A.1中的Image Processing Toolbox函数列表为读者提供了便捷的参考,可以了解到Toolbox中用于图像处理的各种函数,这些函数可能包括但不限于: 1. 图像读取和写入:如imread和imwrite,用于导入和导出图像文件。 2. 图像显示:如imshow,用于在MATLAB环境中显示图像。 3. 图像变换:包括傅立叶变换(fft2)、几何变换(imrotate、imresize)等。 4. 图像滤波:包括卷积(conv2)、高斯滤波(imgaussfilt)等。 5. 图像分割:如区域生长算法(regionprops)、阈值处理(imbinarize)等。 6. 颜色空间转换:如rgb2gray,将RGB图像转换为灰度图像。 附录A.2中列出的MATLAB核心函数则包括了在书中用到的MATLAB基础和高级功能,例如: 1. 数组操作:如索引、切片、矩阵运算等。 2. 控制流:如for循环、if条件语句等。 3. 数据分析:如统计函数(mean、std)、曲线拟合(fit)等。 4. 图形绘制:如plot、histogram用于绘制图像和直方图。 5. 文件I/O:如fprintf和fscanf用于文件读写。 通过书中对这些函数的使用和示例,读者不仅可以掌握MATLAB编程的基本技巧,还能深入了解数字图像处理的理论和应用。同时,对于MATLAB未在书中使用的Toolbox函数,读者可以通过查阅官方文档来获取更全面的信息,以扩展自己的知识库。 《Digital Image Processing Using MATLAB, 2nd Edition》是一本实用的教材,它结合理论与实践,为学习者提供了一个全面的MATLAB图像处理学习平台,是从事图像处理研究和开发的工程师、学者以及学生的重要参考资料。
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本书是DIPUM的第二版,编者Rafael C.Gonzalez。 共压缩成三部分。 注意,需Part1-Part3 三部分都下载了才能解压缩。 (提醒:本书为扫描版,不算清楚,但是也来之不易) For Image and Computer Vision, Image Processing, and Computer Vision courses. This is the first text that provides a balanced treatment of image processing fundamentals and an introduction to software principles used in the practical application of image processing. A seamless integration of material from the leading text, Digital Image Processing by Gonzalez and Woods and the Image Processing Toolbox from Mathworks, Inc. This text works in the MATLAB computing environment; the Toolbox provides a stable, well-supported set of software tools capable of addressing a broad spectrum of applications in digital image processing. The major areas covered include intensity transformations, linear and nonlinear spatial filtering, filtering in the frequency domain, image restoration and registration, color image processing, wavelets, image data compression, morphological image processing, image segmentation, regions and boundary representation and description, and object recognition. From the Back Cover Digital Image Processing Using MATLAB is the first book that provides a balanced treatment of image processing fundamentals and the software principles used in their practical implementation. The book integrates material from the leading text, Digital Image Processing by Gonzalez and Woods, and the Image Processing Toolbox of the MathWorks. Inc., a recognized leader in scientific computing. The Image Processing Toolbox provides a stable, well-supported set of software tools for addressing a broad range of applications in digital image processing. A unique feature of this hook is its emphasis on showing how to enhance those tools by the development of new code. This is important in image processing, where there is a need for extensive experimental work in order to arrive at acceptable problem solutions. After an introduction to the fundamentals of MATLAB programming, the book addresses the mainstream areas of image processing. Areas covered include intensity transformations, linear and nonlinear spatial filtering, filtering in the frequency domain, image restoration and registration, color image processing, wavelets, image data compression, morphological image processing, image segmentation, regions and boundary representation and description, and object recognition.